A Generator Network is a component of a Generative Adversarial Network (GAN) that creates new data instances resembling the training data, aiming to deceive a discriminator network into classifying them as real. It learns to generate realistic data through an adversarial process, improving iteratively by minimizing the difference between generated and real data distributions.