CycleGAN is a type of Generative Adversarial Network (GAN) that facilitates image-to-image translation without requiring paired images for training. For instance, CycleGAN can transform images from one domain (e.g., horses) to another (e.g., zebras) and vice versa. This approach enables creative applications such as style transfer and domain adaptation by learning to map between different visual representations.