NumPy is a library for the Python programming language that provides support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. It was created in 2005 by Travis Oliphant and is an open-source project that can be used freely. NumPy stands for Numerical Python.

NumPy is used in data science, where arrays are frequently used and speed and resources are very important. It is also used in scientific computing with Python. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It provides a high-performance multidimensional array object and tools for working with these arrays.

NumPy arrays are stored at one continuous place in memory, unlike lists, so processes can access and manipulate them very efficiently. This behavior is called locality of reference in computer science. NumPy arrays are also memory efficient as they store homogeneous data in contiguous blocks of memory, where lists can store heterogeneous data.

In summary, NumPy is a powerful library for Python that provides support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. It is widely used in data science and scientific computing due to its efficiency and ease of use.