A Radial Basis Function (RBF) is a real-valued function whose value depends only on the distance from a central point, making it a powerful tool for interpolation in multidimensional space. RBFs are widely used in machine learning for kernel methods, particularly in support vector machines, due to their ability to model complex, non-linear relationships by transforming data into a higher-dimensional space.