This is one of the very nice things about ACBC. For the respondent, the brands that the respondent rejected (prior to the beginning of the ACBC survey) are indeed included in the utility estimation. Additional "synthetic" tasks are added to the data for that respondent, indicating that this respondent compared the rejected brands to the accepted brands, and chose the accepted brands. This informs utility estimation that this respondent strongly dislikes those other brands. But, it allows you to have a complete data set with all brands present for each respondent whereby to conduct market simulations.
I'd suggest you don't look at attribute importance scores. They are not very meaningful, especially in this case.
Preferably, use the market simulator to conduct "sensitivity analysis" on each attribute, so you can see the impact of each attribute on choices (while considering a relevant competitive base case scenario). The ACBC utilities for missing brands are quite appropriate for including in this type of analysis.
If you allow respondents to drop levels of an attribute as inferior, then indeed traditional "importance" scores coming out of ACBC exercises will have lots of weight thrown to attributes that allowed such exclusions.