Introduction: Alexithymia is a multidimensional construct characterized by difficulties in identifying and describing emotions, distinguishing emotional states from bodily sensations, and an externally oriented thinking style. Although the prevalence in the general population is around 10%, it is significantly higher in clinical groups, including those with autism spectrum disorders, depression, anxiety, and neurological conditions. Neuroimaging research, especially using magnetic resonance imaging, has documented structural and functional alterations in alexithymia; however, electroencephalography (EEG)—an older yet temporally precise method—remains less comprehensively explored. This mechanistic review aims to synthesize EEG-based evidence of the neural correlates of alexithymia and to propose potential neurophysiological mechanisms underpinning its affective and cognitive dimensions. Methods: A thorough literature search was conducted in December 2024 across PubMed/Medline, ResearchGate, Google Scholar, and Cochrane using combined keywords (“EEG”, “QEEG”, “electroencephalography”, “alexithymia”) to identify English-language clinical trials or case studies published from January 1980 to December 2024. Two reviewers independently screened the titles and abstracts, followed by a full-text review. Studies were included if they specifically examined EEG activity in participants with alexithymia. Of the 1021 initial records, eight studies fulfilled the inclusion criteria. Results: Across the reviewed studies, individuals with alexithymia consistently demonstrated right-hemisphere dominance in EEG power and connectivity, particularly in the theta and alpha bands, during both neutral and emotion-eliciting tasks. Many exhibited reduced interhemispheric coherence and disrupted connectivity in the frontal and parietal regions, potentially contributing to difficulties in cognitive processing and emotion labeling. Some studies have also reported diminished gamma band activity and phase synchrony in response to negative stimuli, suggesting impaired higher-order integration of emotional information. Crucially, subjective reports (e.g., valence ratings) often do not differ between alexithymic and non-alexithymic groups, highlighting that EEG measures may capture subtle emotional processing deficits not reflected in self-reports. Conclusions: EEG findings emphasize that alexithymia involves specific disruptions in cortical activation and network-level coordination, rather than merely the absence of emotional experiences. Right-hemisphere over-reliance, reduced interhemispheric transfer, and atypical oscillatory patterns in the alpha, theta, and gamma bands appear to be central to the condition’s pathophysiology. Understanding these neural signatures offers avenues for future research—particularly intervention studies that test whether modulating these EEG patterns can improve emotional awareness and expression. These insights underscore the potential clinical utility of EEG as a sensitive tool for detecting and tracking alexithymic traits in both research and therapeutic contexts.