A Fuzzy Inference System (FIS) is a form of artificial intelligence that mimics human reasoning to make decisions based on imprecise or uncertain information. It uses fuzzy logic, which allows for degrees of truth rather than the traditional binary true/false values. This makes FIS particularly useful in situations where data is vague or incomplete. FIS typically consists of three main components: a fuzzification interface that converts crisp inputs into fuzzy values, a rule base that contains a set of fuzzy rules, and a defuzzification interface that transforms fuzzy outputs back into crisp values. This structure enables FIS to handle complex problems in various fields, including control systems and decision-making.