  The application of a zeroth-order scheme for minimising Polyak-\L{}ojasewicz
(PL) functions is considered. The framework is based on exploiting a random
oracle to estimate the function gradient. The convergence of the algorithm to a
global minimum in the unconstrained case and to a neighbourhood of the global
minimum in the constrained case along with their corresponding complexity
bounds are presented. The theoretical results are demonstrated via numerical
examples.
