To empower the general mass through access to information and knowledge, organized efforts are being made to develop relevant content in local languages and provide local language capabilities to utility software. We have developed a Question Answering (QA) System for Hindi documents that would be relevant for masses using Hindi as primary language of education. The user should be able to access information from E-learning documents in a user friendly way, that is by questioning the system in their native language Hindi and the system will return the intended answer (also in Hindi) by searching in context from the repository of Hindi documents. The language constructs, query structure, common words, etc. are completely different in Hindi as compared to English. A novel strategy, in addition to conventional search and NLP techniques, was used to construct the Hindi QA system. The focus is on context based retrieval of information. For this purpose we implemented a Hindi search engine that works on locality-based similarity heuristics to retrieve relevant passages from the collection. It also incorporates language analysis modules like stemmer and morphological analyzer as well as self constructed lexical database of synonyms. The experimental results over corpus of two important domains of agriculture and science show effectiveness of our approach.