The paragraph below summarizes the distinction between algorithmic and statistical perspective of models:
While the data modeling culture assumes that data are generated by an underlying stochastic process, the algorithmic tradition makes no assumptions about the processes that generate data. The algorithmic tradition seeks to uncover patterns in data to identify the processes that produce them. The fact that algorithmic modeling has no explicit probabilistic base raises questions about several sources of bias and about how researchers should deal with them to obtain meaningful results.
From: “New Life for Old Ideas: The ‘Second Wave’ of Sequence Analysis Bringing the ‘‘Course’’ Back Into the Life Course.” Aisenbrey and Fasang.