I think I'll disagree mildly. In "slow" languages like MATLAB and Python/NumPy, often the most performant way to do computation is array primitives. So much so that the style becomes idiomatic over, say, for loops.
I think that it's intuitive for people working with large datasets/numerical data, and not otherwise. You can cheerfully write loops in Python for most problems, except the set of problems solved by Numpy.
Mind you, I cut my teeth on R, so needing to use loops in other languages confused the hell out of me at first.
