Python environments are isolated spaces that allow developers to manage dependencies and packages for different projects without conflicts. Each environment can have its own version of Python and its own set of installed libraries, ensuring that changes in one project do not affect others. This is particularly useful when working on multiple projects that require different package versions or Python interpreters. Common tools for creating and managing Python environments include venv, virtualenv, and conda. Understanding how to effectively use these environments is essential for maintaining a clean and efficient development workflow.