The null hypothesis (H0) in an analysis of variance (ANOVA) is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups.
In the context of a main effect in a two-way ANOVA, H0 would be referring to the effect of one independent variable on the dependent variable, ignoring all other independent variables.
By convention and definition, the null hypothesis for the main effect of an ANOVA is that the samples drawn from the different levels are all from populations with the same mean values. This essentially assumes that the variable that differentiates the levels (what's being analyzed) has no impact on the dependent variable.
The null hypothesis would not be assuming that there are unequal variances (Option A) or equal variances (Option C). The assumption of equal or unequal variances refers to a different aspect in ANOVA, called homogeneity of variances.
The assumption that the scores are normally distributed (Option D) is another separate assumption of ANOVA, known as the normality assumption. Although important, it is not what the null hypothesis for the main effect suggests.
Hence, based on this reasoning, we can conclude that the answer to this question is 'there are equal means', which corresponds to Option B.