Measurable properties or characteristics observed in data, essential for algorithms in pattern recognition, classification, and regression. The selection of informative, discriminating, and independent features is critical to algorithm effectiveness. Typically numeric, features also include structural types like strings and graphs, especially in syntactic pattern recognition. They serve as the foundation for models to learn, identify patterns, and make predictions by analyzing the inherent traits within the data.