Soft Computing is a branch of computer science that deals with approximate solutions rather than fixed and exact answers. It encompasses various techniques such as fuzzy logic, neural networks, and genetic algorithms, which are designed to handle uncertainty and imprecision in data. This approach is particularly useful in real-world applications where traditional methods may struggle. The primary goal of soft computing is to model complex systems and make decisions based on incomplete or uncertain information. By mimicking human reasoning and learning processes, soft computing can improve performance in areas like data analysis, pattern recognition, and machine learning, making it a valuable tool in modern technology.