Natural Language Processing is a domain of research which becomes backbone for Question and Answering application. This interface is retrieving answers to questions, which retrieves from application backend. It leads us to new domain of developing a system which has potential to become useful application. This application comes with higher relatively between Questions and answers. It also gives interactive user interface so that user can easily communicate with it. I took the approach of designing a question answering system that is based on tagging and chunking algorithm, keyword fetch and statistical approach to match keywords classification. Question classification extracts useful information from the question about how to answer the question. Tagging extracts useful information, which will be used in finding the answer to the question. We used different approach to tag the documents. Currently our system classifies the questions using manually developed rules. I also investigated Natural Language Processing algorithms which can use various methods to answer questions and come up with implementation of Maximal Likelihood algorithm. This thesis also includes investigations into modules of a question answering system and gives insights into how to go about developing a question answering system based on tagging and chunking.