Research on pattern recognition began with the advent of computers. The goal of pattern recognition technology is to realize an intelligent machine that can recognize various media such as characters, images, and speech with high accuracy. In other words, it is to realize human’s excellent recognition functions on a computer. The pattern recognition functions of humans are considered to be acquired through learning. Therefore, the research to realize the learning functions by machine, that is, machine learning research, is inseparable from pattern recognition. Although they used to refer to almost the same research field, machine learning has developed on its own and expanded its scope of activities since around 2000. Therefore, machine learning has come to refer to a broader research area, including pattern recognition. However, there is little difference between the two fields if we limit ourselves to the fundamentals that beginners should learn. This chapter describes the basic processes of pattern recognition, namely feature extraction and nearest neighbor rule, and prepares for understanding the learning algorithms introduced in the next chapter.