The sigmoid function is a mathematical function that produces an S-shaped curve, often used in statistics and machine learning. It takes any real-valued number and maps it to a value between 0 and 1. This property makes it particularly useful for modeling probabilities, such as in binary classification tasks. In the context of neural networks, the sigmoid function helps to introduce non-linearity, allowing the model to learn complex patterns. It is commonly used as an activation function, where it determines whether a neuron should be activated based on its input. Other activation functions, like ReLU and tanh, are also popular in this field.