The Softmax Function is often used as the final activation function in a neural network model for classification tasks. It transforms a raw output vector from the model into a series of probabilities, representing the likelihood of each potential class being the correct label. By doing so, it ensures that the probabilities of all classes sum to one, enabling effective interpretation of classification predictions.