Time complexity for accessing an element in an array in Python is O(1).

Explanation:
Accessing an element in an array means retrieving the value of a specific element at a given index. In Python, arrays are implemented as lists, and accessing an element by index in a list has a time complexity of O(1), which means it takes a constant amount of time regardless of the size of the array.

Why is it O(1)?
To understand why accessing an element in an array is O(1) in Python, we need to look at how arrays are implemented in Python.

In Python, lists are implemented as dynamic arrays. A dynamic array is a data structure that automatically resizes itself as elements are added or removed. When a list is created, a contiguous block of memory is allocated to store the elements.

To access an element in a list, Python uses the index of the element to calculate its memory address. Since the memory addresses are contiguous, Python can directly access the element by using simple arithmetic calculation.

The time complexity for accessing an element in an array is O(1) because the time it takes to access an element does not depend on the size of the array. It directly accesses the element's memory address with a constant amount of time.

Example:
Consider the following Python code:

```
my_array = [1, 2, 3, 4, 5]
print(my_array[2])
```

In this example, we are accessing the element at index 2, which is 3. Regardless of the size of the array, accessing this element will take the same amount of time, making the time complexity O(1).

Conclusion:
In Python, accessing an element in an array has a time complexity of O(1) because it directly accesses the element's memory address with a constant amount of time. This makes accessing elements in arrays very efficient, regardless of the size of the array.