The hyperbolic tangent function, or tanh, is an activation function used in neural networks that outputs values between -1 and 1, providing a zero-centered distribution which can help in faster convergence during training. It is particularly useful for handling negative inputs and gradients, reducing the likelihood of issues such as the vanishing gradient problem compared to the sigmoid function.