Decision trees are a powerful tool for understanding and interpreting text data, allowing users to visualize and analyze the relationships between different textual features. By employing decision trees, one can simplify complex data into clear decision-making paths, making it easier to classify and extract valuable insights from text. The article emphasizes the importance of feature selection and tree pruning to enhance the model's performance and accuracy.