What is underfitting in machine learning, and how can it be avoided?

Answer: Underfitting occurs when the model is too simple to capture the underlying pattern in the data, resulting in poor performance both on training and test sets. To avoid underfitting:
* Use more complex models.
* Increase the number of features or include polynomial features.
* Reduce regularization.