ANNs are computational models inspired by the human brain's network of neurons. These models consist of layers of nodes (neurons) that process input data, learn from it, and make predictions or classifications. The key components include input layers, hidden layers, and an output layer. Each node is connected by weighted links, and the weights are adjusted during training to minimize prediction errors.