An Adversarial Network, often called a Generative Adversarial Network (GAN), comprises two neural networks that engage in a competitive process. The Generator creates synthetic data, while the Discriminator assesses whether the data is real or fake. This adversarial setup helps refine the Generator's outputs to produce highly realistic data by constantly challenging and improving its ability to mimic the true data distribution.