The unabated growth of the Web and the increasing expectation placed by the user on the search engine to anticipate and infer his/her information needs and provide relevant results has fostered the development of the field of Web Information Retrieval (Web IR). The recent surveys claim that 85% of internet users use search engines and search services to find specific information [1]. The same surveys, however, show that users are not satisfied with the performance of the current generation search engines. The slow retrieval speed, poor quality of retrieved results, handling a huge quantity of information, addressing subjective & time-varying search needs, finding fresh information and dealing with poor quality queries are commonly cited glitches. This paper expounds the Web Information Retrieval paradigm, a variant of classical Information Retrieval, by illustrating its basics, the components, model categories, tools, tasks and the performance measures that quantify the quality of retrieval results.