ReLU (Rectified Linear Unit) is an activation function used in neural networks that outputs the input directly if it is positive, otherwise, it outputs zero, introducing non-linearity to the model while maintaining computational efficiency. It helps mitigate the vanishing gradient problem and is widely used in deep learning architectures due to its simplicity and effectiveness.