  Non-local correlations are usually understood through the outcomes of
alternative measurements (on two or more parts of a system) that cannot
altogether actually be carried out in an experiment. Indeed, a joint
input/output -- e.g., measurement-setting/outcome -- behavior is non-local if
and only if the outputs for all possible inputs cannot coexist consistently. It
has been argued that this counterfactual view is how Bell's inequalities and
their violations are to be seen. We propose an alternative perspective which
refrains from setting into relation the results of mutually exclusive
measurements, but that is based solely on data actually available. Our approach
uses algorithmic complexity instead of probability, implies non-locality to
have similar consequences as in the probabilistic view, and is conceptually
simpler yet at the same time more general than the latter.
