Feature extraction is a crucial process in machine learning and data analysis that involves transforming raw data into a set of usable features. This technique helps in reducing the dimensionality of the data, making it easier to analyze and interpret. By selecting and creating relevant features from the original dataset, feature extraction enhances model performance and accuracy while minimizing computational complexity. It is widely applied in various domains, including text analysis, image processing, and recommendation systems, where it aids in identifying patterns and insights that drive decision-making and improve user experiences.