I would use a simple additive model, in which the rating of movie $i$ by person $j$ is approximated by the sum of two values, $a_i + b_j$. Least-squares estimates of $a_1,...,a_6$ and $b_1,...,b_6$ can be obtained based on all 32 ratings. There are many ways to do this; I identified the solution by imposing the constraint $\sum b_j=0$. Then, if movies 1,...,5 were rated by all 6 people and movie 6 was rated by only persons 1 & 2, inspection of the symbolic expressions for the estimated ratings $a_6 + b_j,\; j=3,4,5,6$, shows that each estimated rating is given by the sum of a common component plus a component that is specific to person $j$. The person-specific component is the average of person $j$'s ratings of movies 1,...5. The common component is the average rating of movie 6 by persons 1 & 2, minus the average ratings of movies 1,...,5 by persons 1 & 2.