A layer in deep learning is a fundamental building block of neural networks, where computations such as feature extraction and pattern recognition occur. Deep learning models consist of multiple layers, including input, hidden, and output layers, which enable AI systems to learn complex relationships in data for tasks like image recognition and NLP.