  We investigate the computational complexity of mining guarded clauses from
clausal datasets through the framework of inductive logic programming (ILP). We
show that learning guarded clauses is NP-complete and thus one step below the
$\sigma^P_2$-complete task of learning Horn clauses on the polynomial
hierarchy. Motivated by practical applications on large datasets we identify a
natural tractable fragment of the problem. Finally, we also generalise all of
our results to $k$-guarded clauses for constant $k$.
