Decorators in Python is one of the most useful concepts supported by Python. It takes functions as arguments and also has a nested function. They extend the functionality of the nested function. 

In Python, error handling is an essential part of programming to handle exceptions and errors that may occur during the execution of code. Error handling helps to ensure that the program runs smoothly and provides meaningful output to the user.

Python decorators are a way of modifying or enhancing the functionality of existing functions without changing their implementation. They are a powerful tool to manage error handling in Python.

Decorators can be used to handle exceptions raised by a function by wrapping it with a try-except block. This helps to prevent the program from crashing due to unhandled exceptions.

To create a decorator for error handling, the decorator function takes the original function as an argument, wraps it inside a try-except block, and returns the modified function. Here's an example: 

def handle_errors(func):
    def wrapper(*args, **kwargs):
        try:
            return func(*args, **kwargs)
        except Exception as e:
            print(f"An error occurred: {e}")
    return wrapper

In the above code, we define a decorator function handle_errors that takes the original function func as an argument. The decorator function wrapper wraps the original function with a try-except block to catch any exceptions that may occur during the execution of the function.

To use this decorator, we simply add @handle_errors above the definition of the function that we want to handle errors for. For example: 

@handle_errors
def divide(x, y):
    return x / y

Now, when we call the divide function and an exception occurs, the handle_errors decorator catches the exception and prints an error message to the console, rather than letting the program crash.

Overall, using decorators for error handling in Python can help to improve the robustness and reliability of your code, and make it easier to maintain and debug in the long run.