Training data essentially serves as the foundation for building models by providing examples from which the model can learn. It's analogous to how a child learns by observing and practicing from a variety of instances. Training data comprises input-output pairs where the correct answer is known, facilitating the learning process. Its quality, size, and diversity significantly affect model performance and generalization capabilities.