https://www.analyticsvidhya.com/blog/2020/03/6-python-libraries-interpret-machine-learning-models/
What is a model explainer? A model explainer is a function designed to show how the model produces different predictions. Models in 2D are relatively easy to describe. For example, there we could have a classification model determined by a single line.
However, models frequently have more than 2 features, and so cannot be easily placed on a single chart. However, a model explainer can help us answer the following questions. Which features are the most important? How does changing those features impact the prediction? Is the model more complicated than it needs to be?
This information allows us to see inside the Blackbox of what a ML model is doing.