This lecture covers the concept of feature maps, the Representer theorem, kernels, and Reproducing Kernel Hilbert Spaces (RKHS). It explains how any vector can be written as a combination of feature vectors in a high-dimensional space, providing a theoretical foundation for machine learning algorithms.