The Opinion mining is an ongoing field of research and development in web text mining domain. It is the computational treatment of opinions, sentiments and subjectivity of text. This survey paper focus on a comprehensive overview of the Opinion mining algorithms and the different classification with their field of applications. It is the field of computer science in which tools of software that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. As a result, there is a huge volume of opinionated data recorded in digital form for analysis. The current research is focusing on the area of Opinion Mining also called as sentiment analysis. It extracts public opinion about the product via discussion forums, feedbacks, review sites and blogs available in digital form. One main issue in sentiment analysis of product reviews is to produce summary of opinions based on product features. We have surveyed and analyzed in this paper, various techniques that have been developed for the key tasks of opinion mining. This is very useful for the further new researchers in this field to acquire knowledge in opinion mining.