A cost function is an essential part of machine learning algorithms. It is used to measure the accuracy of a model by calculating the difference between the predicted values and the actual values. It is used to optimize the model parameters and reduce the error.

For example, in linear regression, the cost function is defined as the mean squared error (MSE). It is defined as the average of the square of the difference between the predicted values and the actual values. The goal is to minimize the cost function by adjusting the model parameters.